Supervised versions of the PageRank algorithm

Graph-based ranking plays a key role in many applications, such as web search and social computing. PageRank algotithm computes ranking scores relying only on the graph structure. Recently proposed methods, such as Semi-Supervised PageRank, take into account both the graph structure and the metadata associated with nodes and edges. In our talk we will describe some variants of these algorithms and efficient algorithms of tuning their parameters.